The present invention concerns methods of predicting clinical outcomes such as likelihood of mortality or death, new congestive heart failure, new pulmonary congestion or the like in a patient that has received reperfusion therapy such as thrombolytic therapy.
Myocytes contain high intracellular concentrations of biochemical markers that are released into circulation after cell death. Using mathematical functions to model the release of these markers after myocardial infarction (MI) has been under investigation since the early 1970s (S. Witteveen et al., In: Haas J H, Hemker H C, Snellen H A, eds. Ischemic Heart Disease. Baltimore: Williams and Wilkins, 36 (1970); W. Shell et al., J Clin. Invest. 50: 2614 (1971); B. Sobel et al., Circulation 46: 640 (1972); R. Roberts et al., Circulation 52: 743 (1975); S. Witteveen et al., Br Heart J 37:795-(1975); R. Norris et al., Circulation 51: 614 (1975); W. Ryan et al., Am Heart J 101: 162 (1981); P. Grande et al., Circulation 65:756 (1982); L. Ong et al., Am J Cardiol 64:11 (1989); W. Hermens et al., Circulation 81:649 (1990); H. Schwerdt et al., Cardiovasc Res 24:328 (1990)). However, many models have been criticized, because the calculated quantity of biochemical markers released from the intracellular compartment often did not accurately relate to infarct size, commonly expressed in grams of infarcted tissue, in dogs with induced coronary occlusion (C. Roe and C. Starmer, Circulation 52:1 (1975); C. Roe et al., Circulation 55:438 (1977); C. Roe, Clin Chem 23:1807 (1977); Horder et al., Scand J Clin Lab Invest 41:41 (1981); R. Roberts, Circulation 81:707 (1990)). This discordance may have resulted from an incomplete understanding of the complex mechanisms governing the clearance kinetics of biochemical markers after MI. Also, the effects of infarct extension (F. Cobb et al., Circulation 60:145 (1979)) and reperfusion (J. Jarmakani et al., Cardiovasc Res 10:245 (1976); S. Vatner et al., J Clin Invest 61:1048 (1978)) were not accounted for in these methods. Multicompartment models have been used in an attempt to relate empirical observations with the physiological processes of marker release and clearance. Better recovery in terms of grams of infarcted tissue has been reported with use of a two-compartment model for lactate dehydrogenase and creatine kinase (CK) release in permanently occluded canine models.
Although of scientific interest physiologically, calculating the precise amount of biochemical marker released after necrosis may not reflect the primary clinical objective. Additionally, most methods use permanent occlusion models for development; these physiologically-based models may not be appropriate in the thrombolytic era, where the benefit of establishing coronary artery patency has been shown (Gruppo Italiano per lo Studio della Streptochinasi nell""Infarto Miocardico (GISSI), Lancet 1:397-402 (1986); R. Wilcox et al., Lancet 2:525 (1988)(ASSET); ISIS-2 Collaborative Group, Lancet 2:349 (1988); the TIMI Study Group, N Engl J Med 312:932 (1985); The GUSTO Investigators, N Engl J Med 329: 673 (1993); A. Tiefenbrunn and B. Sobel, Fibrinolysis 3:1 (1989)).
In view of the foregoing, there is a need for new ways to predict clinical outcome for a patient after thrombolytic therapy.
A first aspect of the present invention is a method for predicting the clinical outcome for a patient after said patient has received therapy for acute coronary syndromes such as myocardial infarction. The method comprises:
(a) optionally, but preferably, detecting a first variable comprising a serum creatine kinase-MB release curve area in said patient after initiation of therapy;
(b) optionally, but preferably, detecting a second variable comprising a serum creatine kinase-MB release curve maxima in said patient after initiation of therapy; and then
(c) optionally, but preferably, detecting a third variable comprising the slope of the descending portion of the serum creatine kinase-MB release curve after initiation of therapy (wherein a steep slope for said descending portion is a more favorable indicator of clinical outcome than a shallow slope); and
(d) generating a prediction of clinical outcome for said patient from the variables collected above. While the variables noted above are indicated to be optional, it will be appreciated that at least one of the first through third variables must actually be detected and used in the generating step. Preferably at least one of either the second or third variables is actually detected and used in the generating step.
The foregoing and other objects and aspects of the present invention are explained in detail below.